Systemic Integration of Artificial Intelligence in Indonesian Television Using Soft Systems Methodology

The television industry faces significant challenges due to digital disruption, particularly the increasingly widespread penetration of artificial intelligence (AI) technology. AI has the potential to optimize production, distribution, and audience preference analysis, but its implementation faces the complexities of unstructured social systems. This study aims to explore the systemic application of AI using a Soft Systems Methodology (SSM) approach to identify, analyze, and optimize its use in the television industry. The research method used was qualitative with a case study design at a national television station. The SSM process was carried out through seven stages, starting from exploring the problem situation, compiling rich pictures, analyzing CATWOE, and formulating and evaluating corrective actions. Data were collected through literature review, participant observation, and internal document analysis. The results show that SSM is effective in identifying strategic areas for AI optimization, particularly in audience segmentation, content automation, and broadcast management. The resulting framework is flexible, participatory, and responsive to the social dynamics of media organizations. The impact of this research is a contribution to the development of media information systems and technology, as well as expanding the scope of soft methodologies in responding to the challenges of digital transformation in an adaptive and sustainable manner.